Unfortunately, interpreting \(\mathbb {V}[\hat{p}_n]\)  is not straightforward as in addition to the choice of \(\omega _i\)  it depends on both the rating values as well as their order.
Analogous to its use in selection bias  [1]}, [2]}, one can also apply clipping to the bandwagon effect, e.g. \(\hat{\lambda }_i = \max {(\lambda _i, \tau )}\)  s.t. \(\tau >0\) . However, in contrast with IPS, \(\hat{r}_n\)  and \(\hat{p}_n\)  would remain unbiased, though not conditionally unbiased (Corollary ): clipping or misestimation s.t. \(\hat{\lambda }_i\ne \lambda _i\)  may still affect the rate of convergence.
